1. Field of Invention
The inventions described and claimed herein relate to methods and systems for audio signal processing. Specifically, they relate to methods and systems that enhance audio signals and systems incorporating these methods and systems.
2. Discussion of Related Art
Audio signal enhancement is often applied to an audio signal to improve the quality of the signal. Since acoustic signals may be recorded in an environment with various background sounds, audio enhancement may be directed at removing certain undesirable noise. For example, speech recorded in a noisy public environment may have much undesirable background noise that may affect both the quality and intelligibility of the speech. In this case, it may be desirable to remove the background noise. To do so, one may need to estimate the noise in terms of its spectrum; i.e. the energy at each frequency. Estimated noise may then be subtracted, spectrally, from the original audio signal to produce an enhanced audio signal with less apparent noise.
There are various spectral subtraction based audio enhancement techniques. For example, segments of audio signals where only noise is thought to be present are first identified. To do so, activity periods in the time domain may first be detected where activity may include speech, music, or other desired acoustic signals. In periods where there is no detected activity, the noise spectrum can then be estimated from such identified pure noise segments. A replica of the identified noise spectrum is then subtracted from the signal spectrum. When the estimated noise spectrum is subtracted from the signal spectrum, it results in the well-known musical tone phenomenon, due to those frequencies in which the actual noise was greater than the noise estimate that was subtracted. In some traditional spectral subtraction based methods, over-subtraction is employed to overcome this musical tone phenomenon. By subtracting an over-estimate of the noise, many of the remaining musical tones are removed. In those methods, a constant over-subtraction factor is usually adopted. For example, an over-subtraction factor of 3 may be used meaning that the spectrum subtracted from the signal spectrum is three times the estimated noise spectrum in each frequency.